UMTS Network Coverage Hole Detection using Decision Tree Classifier Machine Learning Approach
No Thumbnail Available
Date
2020-02
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Addis Ababa University
Abstract
Due to various innovative mobile services and applications, traffic is constantly increasing
in size and complexity globally and as well as locally in Ethiopia. To fulfill these
requirements in both quality and quantity, a wide range of radio frequency signal coverage
areas are required. One means of satisfying this requirement is proper planning and
devising proper network management during operational phase for network coverage
hole detection for optimization of uncovered area. Measurement collection is a primary
step towards analyzing and optimizing the performance of a telecommunication service.
In this sense, this work aims to present a solution that contributes to reduce costs and
time in network monitoring by exploiting user equipment Measurement Report (MR)
data via the Minimization of Drive Tests (MDT) functionality.
An automatic coverage hole detection based on classification techniques, which is a
Decision Tree (DT) classifier-based approach is used for rule induction to identify
different scenarios of coverage holes and their respective areas for better service delivery
purposes. The main idea is to jointly observe signal strength and signal quality for
effective coverage-hole detection. It uses a new approach to classify four coverage
scenarios such as “good coverage and good quality”, “good coverage but poor quality”,
“poor coverage but good quality”, and “poor coverage and poor quality” in Universal
Mobile Telecommunications System (UMTS) network considering the last three coverage
classes as coverage -hole with different severity levels.
The result showed that the applied model accuracy was 99.98%, and also the proposed
approach could classify the target classes and allows the visualization of network
performance in terms of signal strength and quality associated with a location. All
four coverage scenarios were visibly observed and the results are almost uniform with
validation results found from the driving test (with about 7dB and 1dB difference of
RSCP and Ec/No respectively considering the cumulative distribution function value
of 18%). 77% of coverage areas were classified as good coverage condition.
Description
Keywords
UMTS, Coverage hole, MDT, MR, DT